In many industries, large numbers of documents are disorganized. For example, in the world of home loans, loan documents are commonly disorganized and/or exist only in paper format. Those institutions that must service, underwrite, and/or complete due diligence on loan documents, for example, loan underwriters, investors, loan marketplaces, loan advisors, etc., must convert loan documents to digital format, properly organize, index, and/or name those documents, in order to research and act on them.
Traditional approaches to document organization may include complete human review. For example, a human must review each document and then organize or group the document. For document review of a large number of documents, the review may require many people to complete the task. Additionally, the complete human approach to document organization may be slow.
Other approaches to document organization may include machine learning techniques and systems. A machine learning system may be able to learn from data. Machine learning systems often require human interaction to adjust the system and/or an initial sample data set to train the system. Additionally, many machine learning systems that categorize text documents use keywords and/or key phrases to organize documents.